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Distributed coordination of emergency medical service for angioplasty patients

Distributed coordination of emergency medical service for angioplasty patients In this paper we study the coordination of Emergency Medical Service (EMS) for patients with acute myocardial infarction with ST-segment elevation (STEMI). This is a health problem with high associated mortality. A “golden standard” treatment for STEMI is angioplasty, which requires a catheterization lab and a highly qualified cardiology team. It should be performed as soon as possible since the delay to treatment worsens the patient’s prognosis. The decrease of the delay is achieved by coordination of EMS, which is especially important in the case of multiple simultaneous patients. Nowadays, this process is based on the First-Come-First-Served (FCFS) principle and it heavily depends on human control and phone communication with high proneness to human error and delays. The objective is, therefore, to automate the EMS coordination while minimizing the time from symptom onset to reperfusion and thus to lower the mortality and morbidity resulting from this disease. In this paper, we present a multi-agent decision-support system for the distributed coordination of EMS focusing on urgent out-of-hospital STEMI patients awaiting angioplasty. The system is also applicable to emergency patients of any pathology needing pre-hospital acute medical care and urgent hospital treatment. The assignment of patients to ambulances and angioplasty-enabled hospitals with cardiology teams is performed via a three-level optimization model. At each level, we find a globally efficient solution by a modification of the distributed relaxation method for the assignment problem called the auction algorithm. The efficiency of the proposed model is demonstrated by simulation experiments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

Distributed coordination of emergency medical service for angioplasty patients

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References (30)

Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer International Publishing Switzerland
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Mathematics, general; Computer Science, general; Statistical Physics, Dynamical Systems and Complexity
ISSN
1012-2443
eISSN
1573-7470
DOI
10.1007/s10472-016-9507-9
Publisher site
See Article on Publisher Site

Abstract

In this paper we study the coordination of Emergency Medical Service (EMS) for patients with acute myocardial infarction with ST-segment elevation (STEMI). This is a health problem with high associated mortality. A “golden standard” treatment for STEMI is angioplasty, which requires a catheterization lab and a highly qualified cardiology team. It should be performed as soon as possible since the delay to treatment worsens the patient’s prognosis. The decrease of the delay is achieved by coordination of EMS, which is especially important in the case of multiple simultaneous patients. Nowadays, this process is based on the First-Come-First-Served (FCFS) principle and it heavily depends on human control and phone communication with high proneness to human error and delays. The objective is, therefore, to automate the EMS coordination while minimizing the time from symptom onset to reperfusion and thus to lower the mortality and morbidity resulting from this disease. In this paper, we present a multi-agent decision-support system for the distributed coordination of EMS focusing on urgent out-of-hospital STEMI patients awaiting angioplasty. The system is also applicable to emergency patients of any pathology needing pre-hospital acute medical care and urgent hospital treatment. The assignment of patients to ambulances and angioplasty-enabled hospitals with cardiology teams is performed via a three-level optimization model. At each level, we find a globally efficient solution by a modification of the distributed relaxation method for the assignment problem called the auction algorithm. The efficiency of the proposed model is demonstrated by simulation experiments.

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Apr 20, 2016

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